Stroke is one of the major diseases causing death and disability. While stroke can be hemorrhagic and ischemic, the majority of stroke is ischemic due to a sudden blockage of blood supply to whole or part of the brain. During a stroke, the viability of the ischemic lesion depends on the level and duration of compromised blood flow. Within hours of the onset of a stroke, the ischemic lesion can consist any of the two types of tissues: (1) an infarct core of irreversibly damaged tissue; and (2) a penumbra region with reduced blood flow that is at risk of further infarction, but the tissue is salvageable by quick restoration of blood supply to the region. The process of measuring blood perfusion hence identifying the infarct core and penumbra in acute stroke non-invasively can provide important information to a physician in order to determine an appropriate treatment regime for the patient, such as thrombolytic therapy for an acute ischemic stroke patient.
A number of systems pertaining to depicting the ischemic penumbra and infarct core in acute stroke have been disclosed. In general, the systems involve a contrast agent delivered as an intravascular bolus during a dynamic imaging session such as computerized tomography (CT) or magnetic resonance imaging (MRI). The temporal profile of the image intensity in a pixel or region of interest (ROI) reflects the characteristics of the contrast agent hence the blood passing through the vasculature. The typical method of obtaining quantitative perfusion indices involves several steps including: (a) convert the signal intensity profile to the contrast concentration profile depending on the type of imaging modality; (b) measure the arterial input function (AIF) from a feeding vessel to the tissue of interest; (c) extract the tissue impulse residue function (IRF) from the tissue profile and the AIF using deconvolution; (d) calculate quantitative perfusion indices including cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) using the IRF. It practice, it is difficult to measure the AIF from a blood vessel immediately feeding the tissue of interests. Instead, a global AIFg is often detected from a large blood vessel such as the internal carotid artery (ICA), middle cerebral artery (MCA), or anterior cerebral artery (ACA).
U.S. Pat. No. 6,792,302 describes a method using dynamic CT perfusion for creating penumbra and infarct images. Certain threshold values are applied to the measured cerebral blood flow (CBF) or mean transit time (MTT) to identify the ischemic lesion, which is further classified into lesion into penumbra and infarct by applying certain threshold values to the measured cerebral blood volume (CBV). However, the CBF and CBV values in normal gray matter are higher (usually about 2 to 3 times) than those in normal white matter, applying the same CBV or CBF threshold values to gray matter and white matter may not be able to delineate the penumbra and infarct regions accurately. Further, in the case of major vessel disease such as acute stroke, a measured global AIFg from a large artery is often associated with a delay and dispersion effect before it reaches the ischemic tissue, causing overestimation of the MTT and underestimation of the CBF calculated by the normal deconvolution technique. Hence method using MTT or CBF thresholds for identifying the ischemic lesion has the potential to systematically overestimate the extent of the ischemic lesion and the penumbra.
Another method for evaluating novel stroke treatments using a tissue risk map has been disclosed in International Patent Application (No. PCT/US01/03502), where a GLM algorithm is used combining T2-weighted MRI, DWI, ADC (apparent diffusion coefficient), CBV, CBF and/or MTT measured by diffusion-weighted MRI (DWI) and perfusion-weighted MRI (PWI). Again there is no taking into the account the delay and dispersion effect, hence potential CBF underestimation and MTT overestimation may leads to overestimation of the ischemic lesion and penumbra.
U.S. Pat. No. 5,685,305 describes a MRI method for detection of abnormal blood flow by measuring the “arrival delay map” calculated from the signal intensity curve. Without using de-convolution of an AIF, the “arrival delay map” value can be influenced by the contrast injection rate and patient cardiac output for a specific scan. Hence this parameter is a relative indicator for the region with abnormal blood flow. Further, no dispersion effect has been taken into account, and there is no disclosure about how to identify the ischemic penumbra.
The International Patent Application No PCT/AU2004/000821 (to the present applicant) has disclosed a method for improved perfusion measurements by taking into account the delay and dispersion effect, resulting in more accurate perfusion measurements including CBF, CBV, MTT and DT (arterial delay time). However, there is no disclosure about how to identify the ischemic penumbra.
In addition, perfusion imaging data often has substantial noise fluctuations particularly for dynamic CT perfusion data acquired with protocols of low radiation dosage. The simple threshold method mentioned above may produce false candidate pixels as ischemic penumbra and infarct regions due to image noise. Therefore it is desirable to further apply cluster analysis to discriminate isolated small regions or pixels from larger clusters of connected pixels reflecting the true ischemic lesion.
The present invention seeks to substantially overcome, or at least ameliorate, any one or more of the abovementioned disadvantages.